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评估2018年至2019年海地的结核病治疗结果:一项竞争风险分析。

Evaluating tuberculosis treatment outcomes in Haiti from 2018 to 2019: A competing risk analysis.

作者信息

Raphael Nernst-Atwood, Garraud Pierre Anthony, Roelens Maroussia, Alfred Jean Patrick, Richard Milo, Estill Janne, Keiser Olivia, Merzouki Aziza

机构信息

Institute of Global Health, University of Geneva, Geneva, Switzerland.

Strategic Health Information System, DAI Global LLC, Port-au-Prince, Haiti.

出版信息

IJID Reg. 2024 Mar 13;11:100350. doi: 10.1016/j.ijregi.2024.03.005. eCollection 2024 Jun.

Abstract

OBJECTIVES

This study assesses tuberculosis (TB) treatment outcomes in Haiti.

METHODS

Data from drug-susceptible patients with TB (2018-2019) were analyzed using the Fine & Gray model with multiple imputation.

RESULTS

Of the 16,545 patients, 14.7% had concurrent HIV coinfection, with a 66.2% success rate. The median treatment duration was 5 months, with patients averaging 30 years (with an interquartile range of 22-42 years). The estimated hazard of achieving a successful treatment outcome decreased by 2.5% and 8.1% for patients aged 45 and 60 years, respectively, compared with patients aged 30 years. Male patients had a 6.5% lower estimated hazard of success than their female counterparts. In addition, patients coinfected with HIV experienced a 35.3% reduction in the estimated hazard of achieving a successful treatment outcome compared with those with a negative HIV serologic status.

CONCLUSIONS

Integrated health care approaches should be implemented, incorporating innovative solutions, such as machine learning algorithms combined with geographic information systems and non-conventional data sources (including social media), to identify TB hotspots and high-burden households.

摘要

目的

本研究评估海地的结核病(TB)治疗结果。

方法

使用多重填补的Fine&Gray模型分析了结核病药物敏感患者(2018 - 2019年)的数据。

结果

在16545名患者中,14.7%同时感染了艾滋病毒,成功率为66.2%。治疗持续时间中位数为5个月,患者平均年龄30岁(四分位间距为22 - 42岁)。与30岁的患者相比,45岁和60岁的患者实现成功治疗结果的估计风险分别降低了2.5%和8.1%。男性患者成功的估计风险比女性患者低6.5%。此外,与艾滋病毒血清学状态为阴性的患者相比,艾滋病毒合并感染患者实现成功治疗结果的估计风险降低了35.3%。

结论

应实施综合医疗保健方法,纳入创新解决方案,如将机器学习算法与地理信息系统及非常规数据源(包括社交媒体)相结合,以识别结核病热点地区和高负担家庭。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/001f/10993134/8a68a843a7ea/gr1.jpg

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